A fingerprint collation apparatus which reads the fingerprint of a finger of a user, verifies the fingerprint and authenticates the user is applied to various apparatuses.
As examples of techniques for reading a finger's fingerprint and registering the fingerprint, there are, for instance, a so-called minutiae method and a pattern matching method.
In the minutiae method, during the registration of a fingerprint to be read, for example, a fingerprint image is first binarized and thinned, and feature points such as ridge endings and ridge bifurcations are extracted from the thinned image. Then, a predetermined number of pixels are traced along a thin line from a feature point and this traced section is extracted as a partial thin line, and this partial thin line is converted to a sequence of approximate segments. This operation is repeated as to a predetermined number of feature points, so that a sequence of segments made of a continuation of a plurality of segments is extracted. In such manner, the fingerprint image is converted to the sequence of segments, and the coordinates of points at the opposite ends of each of the segments and the coordinates of positions at each of which one of the segments is joined to the adjacent are registered. In addition, if a feature point is a ridge bifurcation, a similar process is repeated as to each of three branched thin lines. Furthermore, the number of ridges which intersect lines each connecting the opposite ends of different partial thin lines are calculated and registered on the basis of the kinds and the coordinates of partial thin lines, thinned images and feature points (refer to Japanese Patent Laid-Open Application No. 1-50175 (hereinafter referred to as Patent Document 1), for example).
In addition, in the collation of a fingerprint by the minutiae method, after a fingerprint image is binarized and thinned, feature amounts are extracted first. Then, a thin line close in position to one of the registered partial thin lines is selected from the obtained thinned image, the patterns of both are compared and if a degree of mismatch is equal to a certain threshold or lower, it is determined that both are the same. In addition, this alignment is sequentially executed as to the feature points of the image subject to collation, and each time a match is found, the alignment of both is performed. The other partial thin lines are shifted by the amount of shifting at this time, and a similar comparison is performed on each of the partial thin lines. Furthermore, the number of intersecting ridges is calculated from the thinned image subject to collation, and this number is compared with the registered number of intersecting ridges and if the rate of matching is equal or higher than a predetermined value, it is determined that authentication has succeeded (refer to, for example, Patent Document 1).
In addition, in the pattern matching method, the whole or part of a fingerprint image is stored as a registered template.
However, in the pattern matching method, because the whole or part of a fingerprint image is stored as a registered template, the size of the registered template is large and a memory capacity corresponding to this large size is necessary, so that the problem of slow throughput occurs.
In addition, if an acquired fingerprint image is rotated (for example, upside down), the fingerprint image is not easy to collate, so that the problem of insufficient accuracy occurs.
Furthermore, the minutiae method (refer to, for example, Patent Document 1) makes use of information indicative of the number of ridges between feature points in addition to information indicative of the positions, the directions and the kinds of the individual feature points (for example, ridge bifurcations and ridge endings), in order to increase authentication accuracy on the basis of the number of the ridges between the features points. In other words, in this method as well, if authentication accuracy is to be increased, a certain degree of template size becomes necessary. Accordingly, the minutiae method still has the problems of slow throughput, large data amount and insufficient accuracy.